Senior Data Engineer

Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including

Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V

., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV.

• That approach has earned Tatari broad industry recognition, including being named
• Best CTV AdTech Platform in the 8th annual
• MarTech Breakthrough Awards
• , as well as honors from

Digiday

(

Best Connected TV Platform), AdExchanger

(

Most Innovative TV Advertising Technology

), and

Business Insider

(

Hottest AdTech Companies)

. Tatari has also been recognized as the Best Place to Work by

Inc. Magazine

. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era.

As a Senior Data Engineer in our Reporting and Measure pillar, you will design, build and own the large-scale data pipelines that turn high-volume raw data into curated, production-grade datasets powering Tatari’s reporting and measurement products. You will be responsible for taking data products from requirements through tech spec, implementation, validation and production rollout—partnering closely with data science on methodology, backend and frontend engineers on serving layers, and product on requirements.

The ideal candidate will have deep expertise in building and operating ETL pipelines at scale, a strong data quality and validation mindset, and a proven track record of owning datasets end-to-end in a cross-functional environment.

Your skills and experience:

• 5+ years of dedicated experience designing, building and operating production ETL pipelines at scale
• Strong programming skills in Python (or a similar language) and SQL; deep hands-on experience with Spark/PySpark. We use Databricks and Delta Lake here
• Experience with workflow orchestration tools such as Airflow, including DAG design, backfills and failure recovery
• Strong data modeling skills for analytics - curated/gold-layer datasets, schema design, partitioning and data contracts consumed by downstream services

Ongoing interest in agentic developer workflows: testing agent harnesses, building them, agent loop engineering, and similar emerging paradigms. You enjoy learning how they're reshaping the way software gets built.

• A rigorous approach to data quality: validation, reconciliation and methodology comparison as part of shipping any dataset
• Experience debugging distributed data systems - performance tuning, memory issues, and optimizations
• Strong written communication and cross-functional collaboration skills, from tech specs to incident writeups
• Bonus points if you have experience with OLAP stores (e.g., ClickHouse)